Agronomic characterization of anaerobic digestates with near-infrared spectroscopy.

Anaerobic digestion is an increasingly widespread process for organic waste treatment and renewable energy production due to the methane content of the biogas. This biological process also produces a digestate (i.e., the remaining content of the waste after treatment) with a high fertilizing potential. The digestate composition is highly variable due to the various organic wastes used as feedstock, the different plant configurations, and the post-treatment processes used. In order to optimize digestate spreading on agricultural soils by optimizing the fertilizer dose and, thus, reducing environmental impacts associated to digestate application, the agronomic characterization of digestate is essential. This study investigates the use of near infrared spectroscopy for predicting the most important agronomic parameters from freeze-dried digestates. A data set of 193 digestates was created to calibrate partial least squares regression models predicting organic matter, total organic carbon, organic nitrogen, phosphorus, and potassium contents. The calibration range of the models were between 249.8 and 878.6 gOM.kgDM-1, 171.9 and 499.5 gC.kgDM-1, 5.3 and 74.1 gN.kgDM-1, 2.7 and 44.9 gP.kgDM-1 and between 0.5 and 171.8 gK.kgDM-1, respectively. The calibrated models reliably predicted organic matter, total organic carbon, and phosphorus contents for the whole diversity of digestates with root mean square errors of prediction of 70.51 gOM.kgDM-1, 34.84 gC.kgDM-1 and 4.08 gP.kgDM-1, respectively. On the other hand, the model prediction of the organic nitrogen content had a root mean square error of 7.55 gN.kgDM-1 and was considered as acceptable. Lastly, the results did not demonstrate the feasibility of predicting the potassium content in digestates with near infrared spectroscopy. These results show that near infrared spectroscopy is a very promising analytical method for the characterization of the fertilizing value of digestates, which could provide large benefits in terms of analysis time and cost.

Modelling of anaerobic digestion of microalgae biomass: Effect of overloading perturbation.

Anaerobic digestion (AD) of microalgae is an intriguing approach for bioenergy production. The scaling-up of AD presents a significant challenge due to the systematic efficiency losses related to process instabilities. To gain a comprehensive understanding of AD behavior, this study assessed a modified version of the anaerobic digestion model No1 (ADM1) + Contois kinetics to represent microalgae AD impacted by overloading. To this end, two new inhibition functions were implemented: inhibition by acetate for acidogenesis/acetogenesis and total volatile fatty acids for hydrolysis. This proposed ADM1 modification (including Contois kinetics) simulated AD behavior during the stable, disturbed and recovery periods, showing that the inhibition functions described in the original ADM1 cannot explain the AD performance under one of the most common perturbations at industrial scale (overloading). The findings underscore the importance of refining the inhibitions present in original ADM1 to better capture and predict the complexities of microalgae AD against overloading.

Retention time and organic loading rate as anaerobic co-digestion key-factors for better digestate valorization practices: C and N dynamics in soils.

The growing use of anaerobic co-digestion (AcoD) in processing organic waste has led to a significant digestate production. To effectively recycle digestate back into soils, it is crucial to understand how operational variables in the AcoD process influence the conversion of organic matter (OM). To address this, a combination of biochemical fractionation and various soil incubation tests were employed to assess the stability of OM in digestates generated from anaerobic continuous reactors fed with a food waste-hay mixture and operating at different hydraulic retention times (HRT) and organic loading rates (OLR). This study revealed that digester performance and operating parameters impacted carbon dynamics in soils. A decrease in the carbon mineralization in soils when increasing the HRT was reported (48 ± 4 % for 70 days compared to 59 ± 1 % for 42 days). Specific HRT and OLR values were found to be linked to carbon accessibility and complexity, confirming that longer HRT lead to higher OM removal and increased complexity in soluble OM, despite minor discrepancies in relative carbon distribution. Furthermore, comparable rates of nitrogen mineralization in soils were observed for all digestates, consistent with the accessibility of nitrogen from the particulate OM. Nevertheless, AcoD converted substrates with the potential to immobilize nitrogen in soils into fast-acting fertilizers. In summary, this study underscores the importance of controlling the AcoD performances to evaluate the suitability of digestates for sustainable agricultural practices.

Deciphering the contribution of microbial biomass to the properties of dissolved and particulate organic matter in anaerobic digestates.

The recalcitrant structures either from substrate or microbial biomass contained in digestates after anaerobic digestion (AD) highly influence digestate valorization. To properly assess the microbial biomass contribution to the digested organic matter (OM), a combination of characterization methods and the use of various substrate types in anaerobic continuous reactors was required. The use of totally biodegradable substrates allowed detecting soluble microbial products via fluorescence spectroscopy at emission wavelengths of 420 and 460 nm while the protein-like signature was enhanced by the whey protein. During reactors' operation, a transfer of complex compounds to the dissolved OM from the particulate OM was observed through fluorescence applied on biochemical fractionation. Consequently, the fluorescence complexity index of the dissolved OM increased from 0.59-0.60 to 1.06-1.07, whereas it decreased inversely for the extractable soluble from the particulate OM from 1.16-1.19 to 0.42-0.54. Accordingly, fluorescence regional integration showed differences among reactors based on visual inspection and orthogonal partial latent structures (OPLS) analysis. Similarly, the impact of the substrate type and operation time on the particulate OM was revealed by 13C nuclear magnetic resonance using OPLS, providing a good model (R2X = 0.93 and Q2 = 0.8) with a clear time-trend. A high signal resonated at ∼30 ppm attributed to CH2-groups in the aliphatic chain of lipid-like structure besides carbohydrates intensities at 60-110 ppm distinguished the reactor fed with whey protein from the other, which was mostly biomass related. Indeed, this latter displayed a higher presence of peptidoglycan (δH/C: 1.6-2.0/20-25 ppm) derived from microbial biomass by 1H-13C heteronuclear single-quantum coherence (HSQC) nuclear magnetic resonance. Interestingly, the sample distribution obtained by non-metric multidimensional scaling of bacterial communities resembled the attained using 13C NMR properties, opening new research perspectives. Overall, this study discloses the microbial biomass contribution to digestates composition to improve the OM transformation mechanism knowledge.

Predicting the Stability of Organic Matter Originating from Different Waste Treatment Procedures.

Recycling organic wastes into farmland faces a double challenge: increasing the carbon storage of soil while mitigating CO2 emission from soil. Predicting the stability of organic matter (OM) in wastes and treatment products can be helpful in dealing with this contradiction. This work proposed a modeling approach integrating an OM characterization protocol into partial least squares (PLS) regression. A total of 31 organic wastes, and their products issued from anaerobic digestion, composting, and digestion-composting treatment were characterized using sequential extraction and three-dimension (3D) fluorescence spectroscopy. The apportionment of carbon in different fractions and fluorescence spectra revealed that the OM became less accessible and biodegradable after treatments, especially the composting. This was proven by the decrease in CO2 emission from soil incubation. The PLS model successfully predicted the stability of solid digestate, compost, and compost of solid digestate in the soil by using only the characterized variables of non-treated wastes. The results suggested that it would be possible to predict the stability of OM from organic wastes after different treatment procedures. It is helpful to choose the most suitable and economic treatment procedure to stabilize labile organic carbon in wastes and hence minimize CO2 emission after the application of treatment products to the soil.

Intermediate molecular phenotypes to identify genetic markers of anthracycline-induced cardiotoxicity risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex disease whose polygenic component is mainly unidentified. We propose that levels of intermediate molecular phenotypes in the myocardium associated with histopathological damage could explain CDA susceptibility; so that variants of genes encoding these intermediate molecular phenotypes could identify patients susceptible to this complication. A genetically heterogeneous cohort of mice generated by backcrossing (N = 165) was treated with doxorubicin and docetaxel. Cardiac histopathological damage was measured by fibrosis and cardiomyocyte size by an Ariol slide scanner. We determine intramyocardial levels of intermediate molecular phenotypes of CDA associated with histopathological damage and quantitative trait loci (ipQTLs) linked to them. These ipQTLs seem to contribute to the missing heritability of CDA because they improve the heritability explained by QTL directly linked to CDA (cda-QTLs) through genetic models. Genes encoding these molecular subphenotypes were evaluated as genetic markers of CDA in three cancer patient cohorts (N = 517) whose cardiac damage was quantified by echocardiography or Cardiac Magnetic Resonance. Many SNPs associated with CDA were found using genetic models. LASSO multivariate regression identified two risk score models, one for pediatric cancer patients and the other for women with breast cancer. Molecular intermediate phenotypes associated with heart damage can identify genetic markers of CDA risk, thereby allowing a more personalized patient management. A similar strategy could be applied to identify genetic markers of other complex trait diseases.

Intermediate Molecular Phenotypes to Identify Genetic Markers of Anthracycline-Induced Cardiotoxicity Risk.

Cardiotoxicity due to anthracyclines (CDA) affects cancer patients, but we cannot predict who may suffer from this complication. CDA is a complex trait with a polygenic component that is mainly unidentified. We propose that levels of intermediate molecular phenotypes (IMPs) in the myocardium associated with histopathological damage could explain CDA susceptibility, so variants of genes encoding these IMPs could identify patients susceptible to this complication. Thus, a genetically heterogeneous cohort of mice (n = 165) generated by backcrossing were treated with doxorubicin and docetaxel. We quantified heart fibrosis using an Ariol slide scanner and intramyocardial levels of IMPs using multiplex bead arrays and QPCR. We identified quantitative trait loci linked to IMPs (ipQTLs) and cdaQTLs via linkage analysis. In three cancer patient cohorts, CDA was quantified using echocardiography or Cardiac Magnetic Resonance. CDA behaves as a complex trait in the mouse cohort. IMP levels in the myocardium were associated with CDA. ipQTLs integrated into genetic models with cdaQTLs account for more CDA phenotypic variation than that explained by cda-QTLs alone. Allelic forms of genes encoding IMPs associated with CDA in mice, including AKT1, MAPK14, MAPK8, STAT3, CAS3, and TP53, are genetic determinants of CDA in patients. Two genetic risk scores for pediatric patients (n = 71) and women with breast cancer (n = 420) were generated using machine-learning Least Absolute Shrinkage and Selection Operator (LASSO) regression. Thus, IMPs associated with heart damage identify genetic markers of CDA risk, thereby allowing more personalized patient management.

Improving anaerobic digestion mass balance calculations through stoichiometry and usual substrate characterization.

In recent years, anaerobic digestion (AD) of organic waste has raised as a winning strategy to produce energy and organic fertilizer. To optimize such a technology, mass balance is needed to model or simply monitor the process. This paper describes a theoretical framework allowing process indicators to be derived from estimates of organic waste elemental composition. Using a database of 128 typical feedstocks, semi-empirical equations are provided to estimate this elemental composition in case of a missing analysis. Then, a revised stoichiometric reaction of anaerobic digestion is proposed considering biomass yield and nitrogen. Biomass yield induces a more accurate estimation of the ammonia production and the volatile solids (VS) loss. The stoichiometric reaction allows the prediction of biogaz quality and mass loss and a correction factor for VS removal is proposed. The use of real case studies highlights the need to consider this correction (correction factor range: 1.01-1.2), especially for dry AD.

Prediction of organic matter accessibility and complexity in anaerobic digestates.

Further characterization to properly assess the fate of organic matter quality during anaerobic digestion and organic carbon mineralization in soils is required. Organic matter quality based on its accessibility and complexity was employed to successfully classify 28 substrate/digestate pairs through principal components and hierarchical clustering analysis. The two first components explained 58.02% of the variability and four main groups were separated according to the feedstock type. A decrease in the accessibility (16-66%) and an increase in the complexity (34-98%) of the most accessible fractions was noticed. Besides, an increase of non-biodegradable compounds (17-66%) was globally observed after anaerobic digestion. The observed trends in the conversion of organic matter during anaerobic digestion have allowed to fill the gap in the modeling of the anaerobic digestion process chain. Indeed, partial least squares regressions have accurately predicted the organic matter quality of digestates from their inputs (R2 = 0.831, Q2 = 0.593) although the digester operational conditions (temperature and hydraulic retention time) were non-explicative enough. As a novel approach, the predicted digestate quality was used to feed a partial least squares regression model previously developed to predict organic carbon mineralization in soil. The combined models have predicted experimental organic carbon mineralization in soil (R2 = 0.697) with a model quality similar to the model for organic carbon mineralization in soil (R2 = 0.894). This is the first study that has successfully conceived an additional step in the prediction of organic matter fate from raw substrate before anaerobic digestion to soil carbon mineralization.

The impact of biogas digestate typology on nutrient recovery for plant growth: Accessibility indicators for first fertilization prediction.

In recent years, anaerobic digestion of organic waste (OW) is rapidly appearing as a winning waste management strategy by producing energy and anaerobic digestates that can be used as fertilizers in agricultural soils. In this context, the management of the OW treatment process to maximize agro-system sustainability satisfying the crop nutrient demands represents the main goal. To investigate these traits, two protocols to assess the plant availability of digestate nitrogen (N) and phosphorus (P) were evaluated. With this aim, the N and P availability was determined on 8 digestates and 2 types of digestate-based compost from different OW via sequential chemical extractions (SCE). In addition, the digestates were tested in soil incubations and in plant pot tests with Italian ryegrass and compared with chemical fertilizer and a non-amended control soil. The N extracted from digestates via SCE was related to soil N mineralization and plant N recovery. The C: N ratio had negative impact on mineralized N and its recovery in shoots (ShootsN = -0.0085.(C/N)+0.172, r2 = 0.67), whereas water extractable mineral N was positevely related to the root N apparent recovery fraction (N-ARF) with (RootsN = 5E-5.Nsolublemin+0.0138, r2 = 0.53). The shoot P-ARF was positively correlated with the inorganic water extractable fraction of P (ShootsP =0.1153.H2O-Pi-0.2777.H2O-Po+0.0249, r2 = 0.71) whereas the root P-ARF was positively correlated with the less accessible fractions (RootsP = (b)   0.0955.NaHCO3-Po+0.0955.NaOH-Po-0.0584NaHCO3-Pi+0.0128, r2 = 0.8641). Feedstock digestate typology impacted the N and P recovery results leading to a better description of the typology properties and a first nutrients ARF prediction.

Modelling hydrolysis: Simultaneous versus sequential biodegradation of the hydrolysable fractions.

Hydrolysis is considered the limiting step during solid waste anaerobic digestion (including co-digestion of sludge and biosolids). Mechanisms of hydrolysis are mechanistically not well understood with detrimental impact on model predictive capability. The common approach to multiple substrates is to consider simultaneous degradation of the substrates. This may not have the capacity to separate the different kinetics. Sequential degradation of substrates is theoretically supported by microbial capacity and the composite nature of substrates (bioaccessibility concept). However, this has not been experimentally assessed. Sequential chemical fractionation has been successfully used to define inputs for an anaerobic digestion model. In this paper, sequential extractions of organic substrates were evaluated in order to compare both models. By removing each fraction (from the most accessible to the least accessible fraction) from three different substrates, anaerobic incubation tests showed that for physically structured substrates, such as activated sludge and wheat straw, sequential approach could better describe experimental results, while this was less important for homogeneous materials such as pulped fruit. Following this, anaerobic incubation tests were performed on five substrates. Cumulative methane production was modelled by the simultaneous and sequential approaches. Results showed that the sequential model could fit the experimental data for all the substrates whereas simultaneous model did not work for some substrates.

Organic micropollutants' distribution within sludge organic matter fractions explains their dynamic during sewage sludge anaerobic digestion followed by composting.

The simultaneous fate of organic matter and 4 endocrine disruptors (3 polycyclic aromatic hydrocarbons (PAHs) (fluoranthene, benzo(b)fluoranthene, and benzo(a)pyrene) and nonylphenols (NP)) was studied during the anaerobic digestion followed by composting of sludge at lab-scale. Sludge organic matter was characterized, thanks to chemical fractionation and 3D fluorescence deciphering its accessibility and biodegradability. Total chemical oxygen demand (COD) removal was 41% and 56% during anaerobic digestion and composting, respectively. 3D fluorescence highlighted the quality changes of organic matter. During continuous anaerobic digestion, organic micropollutants' removal was 22 ± 14%, 6 ± 5%, 18 ± 9%, and 0% for fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, and nonylphenols, respectively. Discontinuous composting allowed to go further on the organic micropollutants' removal as 34 ± 8%, 31 ± 20%, 38 ± 10%, and 52 ± 6% of fluoranthene, benzo(b)fluoranthene, benzo(a)pyrene, and nonylphenols were dissipated, respectively. Moreover, the accessibility of PAH and NP expressed by their presence in the various sludge organic matter fractions and its evolution during both treatments was linked to both the quality evolution of the organic matter and the physicochemical properties of the PAH and NP; the presence in most accessible fractions explained the amount of PAH and NP dissipated.

Comparison of pre- and inter-stage aerobic treatment of wastewater sludge: Effects on biogas production and COD removal.

The aim of this study was to investigate thermophilic (55°C) aerobic digestion (TAD) as pre- and inter-stage treatment of sludge anaerobic digestion and to analyse the change in organic matter accessibility and complexity. Pre-treatment decreased methane yield (up to -70%), due to oxidation losses whereas inter-stage treatment slightly improved overall methane yield (+2.6%) and total COD removal (+5%) compared to control. Anaerobic degradability and COD removal in the second anaerobic stage significantly increased, by 13-40%. Organic matter fractionation showed that TAD led to an increase in sludge organic matter accessibility in all cases. Organic matter complexity, measured by fluorimetry, increased after TAD pre-treatment whereas it remained constant after inter-stage treatment. TAD was shown to be more efficient if applied to a more recalcitrant substrate and should thus be used as inter-stage treatment to avoid decreasing methane production.

Supplementary data for the biological age linked to oxidative stress modifies breast cancer aggressiveness.

The data presented in this article are related to the research paper entitled "The biological age linked to oxidative stress modifies breast cancer aggressiveness" (M.M. Sáez-Freire, A. Blanco-Gómez, S. Castillo-Lluva, A. Gómez-Vecino, J.M. Galvis-Jiménez, C. Martín-Seisdedos, M. Isidoro-García, L. Hontecillas-Prieto, M.B. García-Cenador, F.J. García-Criado, M.C. Patino-Alonso, P. Galindo-Villardón, J.H. Mao, C. Prieto, A. Castellanos-Martín, L. Kaderali, J. Pérez-Losada). The data shown were obtained from a population of transgenic mice, MMTV-Erbb2/Neu, with different susceptibility to breast cancer and a mixed genetic background generated by backcrossing. It was observed that the aggressiveness of breast cancer negatively correlates with age, being lower in chronologically old mice, similar to what occurs in humans. Given that oxidative stress is associated with tumour susceptibility and the degree of aging, the association between the aggressiveness of breast cancer and multiple intermediate phenotypes directly or indirectly related to oxidative stress was studied. Using a mathematical model, we defined biological age and the degree of aging as the difference between biological and chronological ages. As a result, we observed that biologically old mice predominated among those that developed the disease early on, that is, those that were chronologically young. We then identified the specific and common genetic components of Quantitative Trait loci or QTL associated with different evolution of breast cancer, the intermediate phenotypes related to oxidative stress studied, the biological age and the degree of aging. Lastly, we showed that the expression pattern in the livers of biologically old mice were enriched in signalling pathways related to inflammation and response to infections; whereas the biologically young mice exhibited enriched pathways related to mitochondrial activity. For the explanation and discussion of these data refer to the research article cited above.

The biological age linked to oxidative stress modifies breast cancer aggressiveness.

The incidence of breast cancer increases with age until menopause, and breast cancer is more aggressive in younger women. The existence of epidemiological links between breast cancer and aging indicates that both processes share some common mechanisms of development. Oxidative stress is associated with both cancer susceptibility and aging. Here we observed that ERBB2-positive breast cancer, which developed in genetically heterogeneous ERBB2-positive transgenic mice generated by a backcross, is more aggressive in chronologically younger than in older mice (differentiated by the median survival of the cohort that was 79 weeks), similar to what occurs in humans. In this cohort, we estimated the oxidative biological age using a mathematical model that integrated several subphenotypes directly or indirectly related to oxidative stress. The model selected the serum levels of HDL-cholesterol and magnesium and total AKT1 and glutathione concentrations in the liver. The grade of aging was calculated as the difference between the predicted biological age and the chronological age. This comparison permitted the identification of biologically younger and older mice compared with their chronological age. Interestingly, biologically older mice developed more aggressive breast cancer than the biologically younger mice. Genomic regions on chromosomes 2 and 15 linked to the grade of oxidative aging were identified. The levels of expression of Zbp1 located on chromosome 2, a gene related to necroptosis and inflammation, positively correlated with the grade of aging and tumour aggressiveness. Moreover, the pattern of gene expression of genes linked to the inflammation and the response to infection pathways was enriched in the livers of biologically old mice. This study shows part of the complex interactions between breast cancer and aging.

Methane production and fertilizing value of organic waste: Organic matter characterization for a better prediction of valorization pathways.

Organic wastes are potential sources of both energy as well as crop production fertilizers. Correlations and models, involving organic matter characterization, have been previously described by several authors although there is still a lack in knowledge on the potential of simultaneous predictions of methane and organic fertilizer quality to optimize the wastes treatments. A methodology combining chemical accessibility and fluorescence spectroscopy was used to characterize 82 different organic wastes. Characterization data were compared with the biochemical methane potential (BMP), and with the biodegradable organic carbon obtained by soil incubation (C_bio). High correlations values were observed (R2 of 0.818 for BMP and 0.845 for C_bio). Model coefficients highlighted the differences and similarities between anaerobic and aerobic soil biodegradation, suggesting that anaerobic recalcitrant molecules could enhance soil fertility. This is a first step in the development of a tool for optimising both types of valorisation according to agrosystem needs and constraints.

Development of a soft extraction method for sulfamethoxazole and transformation products from agricultural soils: Effects of organic matter co-extraction on the environmental availability assessment.

The recycling of biosolids and livestock manure in agriculture may lead to the introduction of antibiotic residues, i.e., parent molecule and transformation products, into amended soils. Their fate in soils can be approached through the assessment of their environmental availability. In this work, the environmental availability of sulfamethoxazole (SMX) and three transformation products (N4-acetyl-SMX, 3-amino-5-methylisoxazole, aniline) was assessed in soils amended with sludge compost or cow manure throughout a three-month incubation, using soft extractions with CaCl2, EDTA or cyclodextrin solutions. First, the freeze-storage of soil samples was shown to decrease the SMX extractability. The SMX extractability depended on the initial concentration, the amendment type and the extracting solution at day 0. From 1.9% up to 63% of the SMX total content was initially extractable. The lowest fractions were quantified in EDTA extracts in which the dissolved organic matter was the most complex and responsible for high matrix effects in mass spectrometry compared to CaCl2 extracts. The purification of cyclodextrin extracts highly reduced the matrix effects, but CaCl2 was considered as the most suitable extractant. SMX extractability strongly decreased after the first 8days of incubation to finally reach 0.4-0.8% after 84days, whatever the initial conditions. This high decrease could be related to humification observed through the increasing complexity of extracted dissolved organic matter. Very low levels of transformation products were quantified throughout the incubation period. The low environmental availability of SMX was mainly due to its sorption on soil organic matter and resulted in its low biotransformation in these amended soils.

Fast characterization of solid organic waste content with near infrared spectroscopy in anaerobic digestion.

The development of anaerobic digestion involves both co-digestion of solid wastes and optimization of the feeding recipe. Within this context, substrate characterisation is an essential issue. Although it is widely used, the biochemical methane potential is not sufficient to optimize the operation of anaerobic digestion plants. Indeed the biochemical composition in carbohydrates, lipids, proteins and the chemical oxygen demand of the inputs are key parameters for the optimisation of process performances. Here we used near infrared spectroscopy as a robust and less-time consuming tool to predict the solid waste content in carbohydrates, lipids and nitrogen, and the chemical oxygen demand. We built a Partial Least Square regression model with 295 samples and validated it with an independent set of 46 samples across a wide range of solid wastes found in anaerobic digestion units. The standard errors of cross-validation were 90mgO2⋅gTS-1 carbohydrates, 2.5∗10-2g⋅gTS-1 lipids, 7.2∗10-3g⋅gTS-1 nitrogen and 99mgO2⋅gTS-1 chemical oxygen demand. The standard errors of prediction were 53mgO2⋅gTS-1 carbohydrates, 3.2∗10-2g⋅gTS-1 lipids, 8.6∗10-3g⋅gTS-1 nitrogen and 83mgO2⋅gTS-1 chemical oxygen demand. These results show that near infrared spectroscopy is a new fast and cost-efficient way to characterize solid wastes content and improve their anaerobic digestion monitoring.

Characterisation of the biodegradability of post-treated digestates via the chemical accessibility and complexity of organic matter.

The stability of digestate organic matter is a key parameter for its use in agriculture. Here, the organic matter stability was compared between 14 post-treated digestates and the relationship between organic matter complexity and biodegradability was highlighted. Respirometric activity and CH4 yields in batch tests showed a positive linear correlation between both types of biodegradability (R2=0.8). The accessibility and complexity of organic matter were assessed using chemical extractions combined with fluorescence spectroscopy, and biodegradability was mostly anti-correlated with complexity of organic matter. Post-treatments presented a significant effect on the biodegradability and complexity of organic matter. Biodegradability was low for composted digestates which comprised slowly accessible complex molecules. Inversely, solid fractions obtained after phase separation contained a substantial part of remaining biodegradable organic matter with a significant easily accessible fraction comprising simpler molecules. Understanding the effect of post-treatment on the biodegradability of digestates should help to optimize their valorization.

Fast ADM1 implementation for the optimization of feeding strategy using near infrared spectroscopy.

Optimization of feeding strategy is an essential issue of anaerobic co-digestion that can be greatly assisted with simulation tools such as the Anaerobic Digestion Model 1. Using this model, a set of parameters, such as the biochemical composition of the waste to be digested, its methane production yield and kinetics, has to be defined for each new substrate. In the recent years, near infrared analyses have been reported as a fast and accurate solution for the estimation of methane production yield and biochemical composition. However, the estimation of methane production kinetics requires time-consuming analysis. Here, a partial least square regression model was developed for a fast and efficient estimation of methane production kinetics using near infrared spectroscopy on 275 bio-waste samples. The development of this characterization reduces the time of analysis from 30 days to a matter of minutes. Then, biochemical composition and methane production yield and kinetics predicted by near infrared spectroscopy were implemented in a modified Anaerobic Digestion Model n°1 in order to simulate the performance of anaerobic digestion processes. This approach was validated using different data sets and was demonstrated to provide a powerful predictive tool for advanced control of anaerobic digestion plants and feeding strategy optimization.